Intensity-modulated radiation therapy for early-stage breast cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Radiation therapy (RT) is a standard treatment for non-metastatic breast cancer and is associated with acute and late toxicities. Intensity-modulated RT (IMRT) may decrease toxicity and is convenient for patients. OBJECTIVES: To assess the efficacy and safety of IMRT in women with early stage breast cancer. DESIGN AND SETTING: Systematic review study; Multi-institutional centers. METHODS: Seven databases were searched. Randomized controlled trials (RCT) comparing IMRT with any "non-IMRT" strategies were included. Primary outcomes were local control and acute toxicity. Cochrane Handbook was use to plan and conduct the review, and PRISMA 2020 was used to report results. RESULTS: Five RCT involving 2,556 women (n = 1,283 IMRT; n = 1,274 control arm) were included. Baseline characteristics were similar between trials and arms. Local relapse-free survival rates were not different (hazard-ratio [HR] 0.62; 95%confidence interval [CI] -0.38 to 1.62; P > 0.05); however, IMRT reduced the overall acute toxicity (RR 0.69, 95%CI 0.58 to 0.82; P < 0.00001) and acute moist desquamation (risk-ratio [RR] 0.71, 95%CI 0.60 to 0.82; P < 0.00001). Lymphedema and pneumonitis rates, and survival outcomes were not affected by IMRT. The 2-year telangiectasia rate was decreased with IMRT (RR 0.66, 95%CI 0.47 to 0.93; P = 0.02); however, edema, pain, pigmentation, or fibrosis remained unaffected. IMRT did not improve cosmesis. CONCLUSIONS: IMRT improved acute toxicity and lowered telangiectasia rates, without affecting oncological and aesthetic outcomes. SYSTEMATIC REVIEW REGISTRATION: This review was registered at Cochrane Database of Systematic Reviews 2013, Issue 3. Art. No.: CD010420. https://doi.org/10.1002/14651858.CD010420.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".